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arXiv quant-ph/0604166quant-ph
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局部密度矩阵的相合性是QMA完全的

Consistency of Local Density Matrices is QMA-complete

Yi-Kai Liu

摘要:

假设我们有一个n量子比特系统,我们被给定一个局部密度矩阵rho_1,.,rho_m,其中每个rho_i描述量子位的子集C_i。我们说rho_i是"一致的“,如果存在一些全局状态sigma(在所有n个量子比特上)与子集C_i上的每个rho_i匹配。这推广了边际概率分布一致性的经典概念。证明了局部密度矩阵的一致性判定是QMA完全的(其中QMA是NP的量子模拟)。这给出了QMA中一个很难的问题的有趣例子。我们的证明有点不寻常:本文利用Bertsimas和Vempala提出的基于随机抽样的凸优化算法,从局部哈密顿量出发,给出了一个图灵约化。与经典情况不同,简单的映射约简在这里似乎不起作用。

英文摘要:

Suppose we have an n-qubit system, and we are given a collection of local density matrices rho_1,...,rho_m, where each rho_i describes a subset C_i of the qubits. We say that the rho_i are ``consistent'' if there exists some global state sigma (on all n qubits) that matches each of the rho_i on the subsets C_i. This generalizes the classical notion of the consistency of marginal probability distributions. We show that deciding the consistency of local density matrices is QMA-complete (where QMA is the quantum analogue of NP). This gives an interesting example of a hard problem in QMA. Our proof is somewhat unusual: we give a Turing reduction from Local Hamiltonian, using a convex optimization algorithm by Bertsimas and Vempala, which is based on random sampling. Unlike in the classical case, simple mapping reductions do not seem to work here.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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